CO Cryo-sorption as a Surface-sensitive Spectroscopic Probe of the Active Site Density of Single-atom Catalysts.

Quantifying the number of active sites is a crucial aspect in the performance evaluation of single metal-atom electrocatalysts. A possible realization is using adsorbing gas molecules that selectively bind to the single-atom transition metal and then probing their surface density using spectroscopic tools. Herein, using in situ X-ray photoelectron (XPS) and near edge X-ray absorption fine structure (NEXAFS) spectroscopy, we detect adsorbed CO gas molecules on a FeNC oxygen reduction single atom catalyst.

Room Temperature Hydrogen Atom Scattering Experiments Are Not a Sufficient Benchmark to Validate Electronic Friction Theory.

In the dynamics of atoms and molecules at metal surfaces, electron-hole pair excitations can play a crucial role. In the case of hyperthermal hydrogen atom scattering, they lead to nonadiabatic energy loss and highly inelastic scattering. Molecular dynamics with electronic friction simulation results, based on an isotropic homogeneous electron gas approximation, have previously aligned well with measured kinetic energy loss distributions, indicating that this level of theoretical description is sufficient to describe nonadiabatic effects during scattering.

Dupilumab Treatment for Aspirin-Exacerbated Respiratory Disease in a Real-World Setting: Impact on Quality of Life and Healthcare Utilization.

Background: Patients with aspirin-exacerbated respiratory disease (AERD) have difficult-to-treat asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) and often require treatment with biologic therapy for asthma or CRSwNP. Healthcare utilization in patients with AERD has not been well described since the advent of respiratory biologics.

Objective: To determine real-world healthcare utilization and quality of life among patients with AERD and to understand the impact of dupilumab, a monoclonal antibody targeting the interleukin 4 receptor, on patient-reported health outcomes and healthcare utilization.

Dupilumab rapidly improves eustachian tube dysfunction and otologic symptoms in aspirin-exacerbated respiratory disease.

Patients with aspirin-exacerbated respiratory disease (AERD) frequently experience symptoms consistent with eustachian tube dysfunction (ETD), which can substantially impair patient quality of life. We analyzed a cohort of 98 adult patients with AERD who participated in a longitudinal, survey-based study. By assessing data over 1 year, we established that, in patients with AERD, the ear/facial subdomain of the 22-item Sino-Nasal Outcome Test (SNOT-22) questionnaire could predict performance on the 7-item Eustachian Tube Dysfunction Questionnaire, a validated instrument for the diagnosis of ETD.

First-Principles Nonadiabatic Dynamics of Molecules at Metal Surfaces with Vibrationally Coupled Electron Transfer.

Accurate description of nonadiabatic dynamics of molecules at metal surfaces involving electron transfer has been a long-standing challenge for theory. Here, we tackle this problem by first constructing high-dimensional neural network diabatic potentials including state crossings determined by constrained density functional theory, then applying mixed quantum-classical surface hopping simulations to evolve coupled electron-nuclear motion. Our approach accurately describes the nonadiabatic effects in CO scattering from Au(111) without empirical parameters and yields results agreeing well with experiments under various conditions for this benchmark system.

Integrated workflows and interfaces for data-driven semi-empirical electronic structure calculations.

Modern software engineering of electronic structure codes has seen a paradigm shift from monolithic workflows toward object-based modularity. Software objectivity allows for greater flexibility in the application of electronic structure calculations, with particular benefits when integrated with approaches for data-driven analysis. Here, we discuss different approaches to create deep modular interfaces that connect big-data workflows and electronic structure codes and explore the diversity of use cases that they can enable.

Predicting Long-Time-Scale Kinetics under Variable Experimental Conditions with Kinetica.jl.

Predicting the degradation processes of molecules over long time scales is a key aspect of industrial materials design. However, it is made computationally challenging by the need to construct large networks of chemical reactions that are relevant to the experimental conditions that kinetic models must mirror, with every reaction requiring accurate kinetic data. Here, we showcase , a new software package for constructing large-scale chemical reaction networks in a fully automated fashion by exploring chemical reaction space with a kinetics-driven algorithm; coupled to efficient machine-learning models of activation energies for sampled elementary reactions, we show how this approach readily enables generation and kinetic characterization of networks containing ∼10 chemical species and ≃10-10 reactions.

Structure of Graphene Grown on Cu(111): X-Ray Standing Wave Measurement and Density Functional Theory Prediction.

We report the quantitative adsorption structure of pristine graphene on Cu(111) determined using the normal incidence x-ray standing wave technique. The experiments constitute an important benchmark reference for the development of density functional theory approximations able to capture long-range dispersion interactions. Electronic structure calculations based on many-body dispersion-inclusive density functional theory are able to accurately predict the absolute measure and variation of adsorption height when the coexistence of multiple moiré superstructures is considered.

Detection of PRRSV-1 in tongue fluids under experimental and field conditions and comparison of different sampling material for PRRSV sow herd monitoring.

Background: Infection with porcine reproductive and respiratory syndrome virus (PRRSV) leads to significant economic losses worldwide. One of the initial measures following an outbreak is to stabilise the herd and to prevent vertical transmission of PRRSV. The objective of this study was to detect PRRSV in different sampling material, both in an experimental model and on a commercial piglet producing farm, with a focus on evaluating the suitability of tongue fluid samples.

Electrostatic potentials of atomic nanostructures at metal surfaces quantified by scanning quantum dot microscopy.

The discrete and charge-separated nature of matter - electrons and nuclei - results in local electrostatic fields that are ubiquitous in nanoscale structures and relevant in catalysis, nanoelectronics and quantum nanoscience. Surface-averaging techniques provide only limited experimental access to these potentials, which are determined by the shape, material, and environment of the nanostructure. Here, we image the potential over adatoms, chains, and clusters of Ag and Au atoms assembled on Ag(111) and quantify their surface dipole moments.

Probing the role of surface termination in the adsorption of azupyrene on copper.

The role of the inorganic substrate termination, within the organic-inorganic interface, has been well studied for systems that contain strong localised bonding. However, how varying the substrate termination affects coordination to delocalised electronic states, like that found in aromatic molecules, is an open question. Azupyrene, a non-alternant polycyclic aromatic hydrocarbon, is known to bind strongly to metal surfaces through its delocalised π orbitals, thus yielding an ideal probe into delocalised surface-adsorbate interactions.

High-throughput property-driven generative design of functional organic molecules.

The design of molecules and materials with tailored properties is challenging, as candidate molecules must satisfy multiple competing requirements that are often difficult to measure or compute. While molecular structures produced through generative deep learning will satisfy these patterns, they often only possess specific target properties by chance and not by design, which makes molecular discovery via this route inefficient. In this work, we predict molecules with (Pareto-)optimal properties by combining a generative deep learning model that predicts three-dimensional conformations of molecules with a supervised deep learning model that takes these as inputs and predicts their electronic structure.

Validation of a questionnaire assessing smell loss in an international aspirin-exacerbated respiratory disease population.

Olfactory dysfunction (OD) and smell loss affects aspects of patients' everyday life and lowers their quality of life. OD questionnaires are considered one of the core-outcome measures in chronic rhinosinusitis, but many existing smell loss questionnaires contained pandemic-prohibitive questions on social gatherings or restaurant visits, were too culture specific or gender specific, or were overly long and cumbersome. We aimed to develop a new brief questionnaire to assess the impact and consequences of smell loss and its burden on daily life.

Machine Learning Interatomic Potentials for Reactive Hydrogen Dynamics at Metal Surfaces Based on Iterative Refinement of Reaction Probabilities.

The reactive chemistry of molecular hydrogen at surfaces, notably dissociative sticking and hydrogen evolution, plays a crucial role in energy storage and fuel cells. Theoretical studies can help to decipher underlying mechanisms and reaction design, but studying dynamics at surfaces is computationally challenging due to the complex electronic structure at interfaces and the high sensitivity of dynamics to reaction barriers. In addition, ab initio molecular dynamics, based on density functional theory, is too computationally demanding to accurately predict reactive sticking or desorption probabilities, as it requires averaging over tens of thousands of initial conditions.

libMBD: A general-purpose package for scalable quantum many-body dispersion calculations.

Many-body dispersion (MBD) is a powerful framework to treat van der Waals (vdW) dispersion interactions in density-functional theory and related atomistic modeling methods. Several independent implementations of MBD with varying degree of functionality exist across a number of electronic structure codes, which both limits the current users of those codes and complicates dissemination of new variants of MBD. Here, we develop and document libMBD, a library implementation of MBD that is functionally complete, efficient, easy to integrate with any electronic structure code, and already integrated in FHI-aims, DFTB+, VASP, Q-Chem, CASTEP, and Quantum ESPRESSO.

Helping patients choose between pain control options for outpatient procedural abortion at less than 12 weeks' gestation.

Objectives: This study aimed to identify predictors of patient satisfaction with their chosen pain control regimen for procedural abortion at <12 weeks' gestation in the outpatient setting.

Study Design: In this prospective cohort study, we developed an instrument to evaluate predictors of satisfaction with pain control regimens among patients choosing local anesthesia alone (paracervical block with 20 mL of 1% buffered lidocaine) or local anesthesia plus intravenous (IV) moderate sedation with 100 mcg of fentanyl and 2 mg of midazolam. Our primary outcome was to identify predictors of satisfaction with both anesthesia cohorts as measured on a 4-point Likert scale, but due to high satisfaction levels in the IV group, we focused our analysis on the local anesthesia group.

Physical and psychological recovery after vaginal childbirth with and without epidural analgesia: A prospective cohort study.

Background: Enhanced recovery is the gold standard in modern perioperative management, including that for cesarean deliveries. However, qualitative and quantitative data on the physical and psychological recovery of women after vaginal childbirth are limited. Whether neuraxial labor analgesia influences postpartum recovery is unknown.

Risks of Powder Flow Obstruction in Hopper and Bin Discharge in Solid Dosage Form Manufacture should be Predicted Under The Active Stress State.

Discharge of powder from a hopper or bin is a common operation in solid dosage form manufacture. Powder flow obstruction during hopper/bin discharge, such as arching or ratholing, remains an outstanding risk and cannot be reliably diagnosed using the existing flow function coefficient-based method. In this study, we showed that the major principal stress (σ) at the bin outlet is required for an accurate prediction of powder flow obstruction risks.

Stability of Single Gold Atoms on Defective and Doped Diamond Surfaces.

Polycrystalline boron-doped diamond (BDD) is widely used as a working electrode material in electrochemistry, and its properties, such as its stability, make it an appealing support material for nanostructures in electrocatalytic applications. Recent experiments have shown that electrodeposition can lead to the creation of stable small nanoclusters and even single gold adatoms on the BDD surfaces. We investigate the adsorption energy and kinetic stability of single gold atoms adsorbed onto an atomistic model of BDD surfaces by using density functional theory.

Assessing Mixed Quantum-Classical Molecular Dynamics Methods for Nonadiabatic Dynamics of Molecules on Metal Surfaces.

Mixed quantum-classical (MQC) methods for simulating the dynamics of molecules at metal surfaces have the potential to accurately and efficiently provide mechanistic insight into reactive processes. Here, we introduce simple two-dimensional models for the scattering of diatomic molecules at metal surfaces based on recently published electronic structure data. We apply several MQC methods to investigate their ability to capture how nonadiabatic effects influence molecule-metal energy transfer during the scattering process.

Behavior of host-cell-protein-rich aggregates in antibody capture and polishing chromatography.

Recent work has shown that aggregates in monoclonal antibody (mAb) solutions may be made up not just of mAb oligomers but can also harbor hundreds of host-cell proteins (HCPs), suggesting that aggregate persistence through downstream purification operations may be related to HCP clearance. We have examined this in a primary analysis of aggregate persistence through processing steps that are typically implemented for HCP reduction, demonstrating that the phenomenon is relevant to depth filtration, protein A chromatography and flow-through anion-exchange (AEX) polishing. Confocal laser scanning microscopy observations show that aggregates compete with the mAb to adsorb specifically in protein A chromatography and that this competitive interaction is integral to the efficacy of protein A washes.

An implementation evaluation of the physical activity counseling for in-patients with major depressive disorder (PACINPAT) intervention: a randomized controlled trial.

Background: The physical activity counseling for in-patients with major depression (PACINPAT) randomized controlled trial was launched to tackle physical inactivity for in-patients with major depressive disorder. Evidence shows that despite potential treatment effects, physical inactivity is prevalent in this population. To contribute to the assessment of how this in-person and remote, theory-based, individually tailored intervention was designed, received and effected behavior, the aim of this study was to evaluate its implementation.

Analytical characterization of host-cell-protein-rich aggregates in monoclonal antibody solutions.

Host-cell proteins (HCPs) and high molecular weight (HMW) species have historically been treated as independent classes of impurities in the downstream processing of monoclonal antibodies (mAbs), but recent indications suggest that they may be partially linked. We have explored this connection with a shotgun proteomic analysis of HMW impurities that were isolated from harvest cell culture fluid (HCCF) and protein A eluate using size-exclusion chromatography (SEC). As part of the proteomic analysis, a cross-digest study was performed in which samples were analyzed using both the standard and native digest techniques to enable a fair comparison between bioprocess pools.